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Features generation and spotting methods and systems using same

a technology of feature generation and feature detection, applied in the field of image processing, analysis, classification, comparison, detection, can solve the problems of irrevocably losing, low false rejection rate, computationally intensive and sensitive to image quality,

Inactive Publication Date: 2009-03-05
XEROX CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The patent describes an image analyzer and method that can divide an image into smaller parts with specific pixel counts. The analyzer uses a recursion processor to find new partition points and applies the image partitioner to create additional sub-images. The resulting features representation of the image is then used to classify it based on the new partition points. The technical effect of this invention is improved image analysis and classification with more accurate and reliable results.

Problems solved by technology

OCR has numerous advantages, but is computationally intensive and sensitive to image quality.
In such an arrangement, any fast rejection stage should produce a low rate of false rejections since any false rejection is not passed onto the downstream stage and hence is irrevocably lost.
However, these features are not strongly discriminatory and tend to produce high false positive rates in the initial classifier.
For example, the aspect ratio feature is highly discriminatory for words of interest that have an unusual aspect ratio, but is less effective for “typical” words that have typical aspect ratios similar to numerous other words.
On the other hand, localized features computed using a sliding window or the like can be strongly discriminatory, but are computationally intensive, and therefore typically not well suited for use in an initial fast rejection stage of a cascaded classifier.

Method used

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  • Features generation and spotting methods and systems using same
  • Features generation and spotting methods and systems using same
  • Features generation and spotting methods and systems using same

Examples

Experimental program
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Embodiment Construction

[0017]With reference to FIG. 1, an illustrative spotting system includes a document image segmentor 10 that segments a document 12 in image form based on whitespaces or other criteria to extract images 14 corresponding to words or other objects in the document 12. The document image segmentor 10 operates in image space, and its operation generally does not entail OCR. The document image 12 may have been generated or acquired by optical scanning, by a digital camera, by software that outputs textual content in an image format, or so forth. An image selector 16 selects one of the images 14 for processing. In some embodiments, the image selector 16 may perform additionally perform selected image pre-processing, such as converting the image to a gradient image, adjusting resolution, performing pixel value inversion (e.g., to convert a negative image to a positive image), converting from RGB or another color system to a grayscale representation, or so forth.

[0018]A two-dimensional recurs...

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PUM

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Abstract

An image partitioner is configured to find a partition point that divides a received image into four sub-images each having a pre-selected activated pixel count. A recursion processor is configured to (i) apply the image partitioner to an input image to generate a first partition point and four sub-images and to (ii) recursively apply the image partitioner to at least one of the four sub-images for at least one recursion iteration to generate at least one additional partition point. A formatter is configured to generate a features representation of the input image in a selected format. The features representation is based at least in part on the partition points. The features representation can be used in various ways, such as by a classifier configured to classify the input image based on the features representation.

Description

BACKGROUND[0001]The following relates to the image processing, analysis, classification, comparison, detection, and related arts. The following is described with illustrative reference to spotting applications such as word spotting, logo spotting, signature spotting, and so forth, but will be useful in numerous other applications.[0002]Optical character recognition (OCR) is a known technique for converting an optically scanned handwritten or typed document to an ASCII, XML, or other text-based format. Existing commercial OCR products include, for example, FineReader™ (available from ABBYY USA Software House, Fremont, Calif.). The OCR converted document is readily searched for words of interest. OCR has numerous advantages, but is computationally intensive and sensitive to image quality.[0003]Word spotting (or, more generally, spotting, which can apply to words, objects such as logos, signatures, and so forth, sometimes also referred to as word detection, logo detection or so forth o...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): G06K9/20G06V30/10
CPCG06K2209/25G06K9/6212G06V2201/09G06V30/10G06V30/18086G06V30/19073
Inventor BLESSAN, MARCOWILLIAMOWSKI, JUTTA KATHARINA
Owner XEROX CORP
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